Evidence map›Paper›PMID 30607307›Full record

ReviewJournal of pathology informatics2018

Twenty Years of Digital Pathology: An Overview of the Road Travelled, What is on the Horizon, and the Emergence of Vendor-Neutral Archives.

Liron Pantanowitz, Ashish Sharma, Alexis B Carter, Tahsin Kurc, Alan Sussman, Joel Saltz

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Journal of pathology informatics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 126 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
126citing papers in PubMed, 3 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

126 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Guideline
  2. Pooled it
  3. Guideline
  4. Article
  5. Review
  6. Review
  7. Article
  8. Review
  9. Article
  10. Review
  11. Article
  12. Digital Pathology in Hematopathology: From Vision to Deployment.International journal of laboratory hematology · 2026
    Review
  13. Review
  14. Review
  15. Article
  16. Article
  17. Review
  18. Review
  19. Article
  20. Article

66 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Liron PantanowitzDepartment of Pathology, University of Pittsburgh Medical Center, Pittsburgh, PA, USA.
Ashish SharmaDepartment of Biomedical Informatics, Emory University, GA, USA.
Alexis B CarterDepartment of Pathology and Laboratory Medicine, Children's Healthcare of Atlanta, GA, USA.
Tahsin KurcDepartment of Biomedical Informatics, Stony Brook University, Stony Brook, NY, USA.
Alan SussmanDepartment of Computer Science, University of Maryland, College Park, MD, USA.
Joel SaltzDepartment of Biomedical Informatics, Stony Brook University, Stony Brook, NY, USA.

Funding

TCIA Sustainment and Scalability - Platforms for Quantitative Imaging Informatics in Precision MedicineU24CA215109 · NCI · UNIV OF ARKANSAS FOR MED SCIS · PI BANERJEE, IMON, PRIOR, FRED WILLIAM · 2017 to 2021
$8.5M
Tools to Analyze Morphology and Spatially Mapped Molecular DataU24CA180924 · NCI · STATE UNIVERSITY NEW YORK STONY BROOK · PI SALTZ, JOEL H. · 2014 to 2019
$3.6M
NCI NIH HHS U24 CA180924NCI NIH HHS U24 CA215109
6 · The paper itself

Abstract

Almost 20 years have passed since the commercial introduction of whole-slide imaging (WSI) scanners. During this time, the creation of various WSI devices with the ability to digitize an entire glass slide has transformed the field of pathology. Parallel advances in computational technology and storage have permitted rapid processing of large-scale WSI datasets. This article provides an overview of important past and present efforts related to WSI. An account of how the virtual microscope evolved from the need to visualize and manage satellite data for earth science applications is provided. The article also discusses important milestones beginning from the first WSI scanner designed by Bacus to the Food and Drug Administration approval of the first digital pathology system for primary diagnosis in surgical pathology. As pathology laboratories commit to going fully digitalize, the need has emerged to include WSIs into an enterprise-level vendor-neutral archive (VNA). The different types of VNAs available are reviewed as well as how best to implement them and how pathology can benefit from participating in this effort. Differences between traditional image algorithms that extract pixel-, object-, and semantic-level features versus deep learning methods are highlighted. The need for large-scale data management, analysis, and visualization in computational pathology is also addressed.

Indexed as

Computational pathologydigital pathologyimage analysisinformaticsvendor neutral archivewhole-slide image

Identifiers

PMID30607307
PMCPMC6289005

What Socratic holds

Textmetadata
LicenceCC BY-NC-SA
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.